Mauro Birattari, et al.  Home/Search
Context Related
| iridia.ulb.ac.be/~...epATRH301.ps.gz Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: iridia.ulb.ac.b...my_publications (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: This paper develops the formal framework of ant programming with the goal of gaining a deeper understanding on ant colony optimization, a heuristic method for combinatorial optimization problems inspired by the foraging behavior of ants. Indeed, ant programming allows a deeper insight into the general principles underlying the use of an iterated Monte Carlo approach for the multi-stage solution of a combinatorial optimization problem. (Update)
Similar documents based on text: More All
0.3: On Solving Permutation Scheduling Problems with Ant Colony.. - Merkle, Middendorf (Correct)
0.3: Toward the formal foundation of Ant Programming - Birattari, Di Caro, Dorigo (2002) (Correct)
0.2: Application of Ant Colony Optimization to Data Distribution in.. - Rodrigues (Correct)
BibTeX entry: (Update)
M. Birattari, G. Di Caro, and M. Dorigo. For a formal foundation of the Ant Programming approach to combinatorial optimization. Part 1: The problem, the representation, and the general solution strategy. Technical Report TR-H-301, ATR Human Information Processing Research Laboratories, Kyoto, Japan, 2000. http://citeseer.ist.psu.edu/birattari00for.html More
@misc{ birattari00formal,
author = "M. Birattari and G. Di Caro and M. Dorigo",
title = "a formal foundation of the Ant Programming approach to combinatorial optimization",
text = "M. Birattari, G. Di Caro, and M. Dorigo. For a formal foundation of the
Ant Programming approach to combinatorial optimization. Part 1: The problem,
the representation, and the general solution strategy. Technical Report
TR-H-301, ATR Human Information Processing Research Laboratories, Kyoto,
Japan, 2000.",
year = "2000",
url = "citeseer.ist.psu.edu/birattari00for.html" }
Citations (may not include all citations):658 Learning from Delayed Rewards (context) - Watkins - 1989
408 Princeton University Press (context) - Bellman - 1957
278 Dynamic Programming and Optimal Control (context) - Bertsekas - 1995
251 The Ant System: Optimization by a colony of cooperating agen.. - Dorigo, Maniezzo et al. - 1996
189 Reinforcement Learning (context) - Sutton, Barto - 1998
157 Ant Colony System: A cooperative learning approach to the tr.. - Dorigo, Gambardella - 1997
112 The ant colony optimization meta-heuristic - Dorigo, Di Caro - 1999
80 Ant algorithms for discrete optimization - Dorigo, Di Caro et al. - 1999
60 Positive feedback as a search strategy - Dorigo, Maniezzo et al. - 1991
46 La reconstruction du nid et les coordinations interindividue.. (context) - Grass - 1959
21 Inspiration for optimization from social insect behavior (context) - Bonabeau, Dorigo et al. - 2000
20 Dipartimento di Elettronica (context) - Dorigo, Learning et al. - 1992
20 Swarm Intelligence: From Natural to Arti cial Systems (context) - Bonabeau, Dorigo et al. - 1999
14 A graph-based Ant System and its convergence (context) - Gutjahr - 2000
12 turns in the selection of the shortest path by the ant Lasiu.. (context) - Beckers, Deneubourg et al. - 1992
[Article contains additional citations not shown here]
Documents on the same site (http://iridia.ulb.ac.be/~gdicaro/my_publications.html): More
Real-time Parallel Computation of Disparity and.. - Valentinotti, Di.. (1996) (Correct)
Two Ant Colony Algorithms For Best-Effort Routing In Datagram .. - Di Caro, Dorigo (1998) (Correct)
Mobile Agents for Adaptive Routing - Di Caro, Dorigo (1998) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC